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Record W2163428288 · doi:10.3390/brainsci3031244

Representation of Linguistic Information Determines Its Susceptibility to Memory Interference

2013· article· en· W2163428288 on OpenAlexaff
Myra A. Fernandes, Jeffrey D. Wammes, Janet H. Hsiao

Bibliographic record

VenueBrain Sciences · 2013
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Waterloo
FundersUniversity of Hong Kong
KeywordsTask (project management)Representation (politics)PsychologyDual (grammatical number)PhonologySearch engine indexingComputer scienceLinguisticsCognitive psychologyNatural language processingCommunicationArtificial intelligence

Abstract

fetched live from OpenAlex

We used the dual-task paradigm to infer how linguistic information is represented in the brain by indexing its susceptibility to retrieval interference. We measured recognition memory, in bilingual Chinese-English, and monolingual English speakers. Participants were visually presented with simplified Chinese characters under full attention, and later asked to recognize them while simultaneously engaging in distracting tasks that required either phonological or visuo-spatial processing of auditorily presented letters. Chinese speakers showed significantly greater memory interference from the visuo-spatial than phonological distracting task, a pattern that was not present in the English group. Such a pattern suggests that retrieval of simplified Chinese characters differentially requires visuo-spatial processing resources in Chinese speakers; these are compromised under dual-task conditions when such resources are otherwise engaged in a distracting task. In a secondary analysis, we showed the complementary pattern in a group of English speakers, whose memory for English words was disrupted to a greater degree from the phonological than visuo-spatial distracting task. Together, these results suggest the mode of representation of linguistic information can be indexed behaviorally by susceptibility to retrieval interference that occurs when representations overlap with resources required in a competing task.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.370
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2013
Admission routes1
Has abstractyes

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